Dynamic contrast enhanced MRI (DCEMRI) has potential to provide critical information to guide therapy and improve outcomes for prostate cancer (PCa) patients. However, sensitivity and specificity are not yet adequate for routine clinical use. DCEMRI has not been demonstrated to reliably differentiate between high Gleason score cancers and low Gleason score cancers. It is not known whether poor diagnostic accuracy is due to measurement error or to underlying biological variability. While a wide range of methods have been proposed to improve DCEMRI, there have been few attempts to validate these methods against gold standards, to determine whether contrast dynamics are accurately measured. To address these problems, we propose to a) Develop innovative quantitative approaches to DCEMRI that have the potential to increase diagnostic accuracy. b) Test DCEMRI against 'gold standards', to determine accuracy and variability, and guide the development of improvements that reduce error. c) Determine whether quantitative DCEMRI can improve discrimination of high Gleason grade from low Gleason grade cancers. We propose the following specific aims: 1. Quantitatively measure contrast media concentration, arterial input function, and physiological parameters (e.g. Ktrans) using innovative approaches developed at the University of Chicago. 2. Validate measurements of contrast media concentration, the arterial input function, Ktrans, and ve, using gold standard measurements, including dynamic contrast enhanced CT, direct measurements of blood concentration of contrast media, and measurements of cardiac output. 3. Evaluate variability of parameters extracted from DCEMRI data. Identify sources of variability - based on the gold-standard measurements and modify procedures to minimize variability. 4. Correlate Gleason grade with quantitative DCEMRI results. 5. Establish a curated imaging database consisting of registered multiparametric in vivo MRI, gold standard measurements, and in vitro histological images. This includes data from DCEMRI, diffusion- weighted-imaging (DWI), CT, calibration scans, parameters from quantitative analysis, and histology. This will provide researchers at other institutions with a valuable database that can be used to test quantitative analysis methods. The proposed research will provide validated DCEMRI methods that improve diagnosis and staging of Pca, and will also impact other applications of DCEMRI. The research will provide important resources for the prostate cancer research community, as evidenced by letters of support by internationally recognized experts. In addition, the collaboration with Philips Medical Systems (see letter of support) will insure rapid translation of results to clinical practice.